2018
DOI: 10.1111/manc.12235
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China’s Fiscal Multiplier and Its State Dependence

Abstract: This paper studies the effects of government spending on China’s output with a threshold structural vector autoregressive model. The empirical findings suggest that increasing government expenditure significantly raises China’s aggregate output. Contrary to the evidence of countercyclical fiscal multipliers in the advanced economies, China’s fiscal multiplier tends to be procyclical, suggesting a novel fiscal policy transmission mechanism in China.

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Cited by 10 publications
(4 citation statements)
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“…The positive responses of government revenue, industrial production and CPI are consistent with the strong domestic stimulative effects of China's government spending found in recent empirical studies (e.g. Chen & Liu, 2018; Zhang et al., 2019). In the absence of monthly consumption data, the retail sales of consumer goods indicator is used as a proxy.…”
Section: Estimation Resultssupporting
confidence: 85%
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“…The positive responses of government revenue, industrial production and CPI are consistent with the strong domestic stimulative effects of China's government spending found in recent empirical studies (e.g. Chen & Liu, 2018; Zhang et al., 2019). In the absence of monthly consumption data, the retail sales of consumer goods indicator is used as a proxy.…”
Section: Estimation Resultssupporting
confidence: 85%
“…The first column in each figure shows the estimated impulse responses of China's economic indicators based on the earlier period, the second column shows the estimated impulse responses based on the later period, and the third column shows their differences.In both periods, the unexpected expansion of government spending effectively boosts domestic demand, leading to a significant increase in government revenue, industrial production, CPI, retail sales and trade deficit. The positive responses of government revenue, industrial production and CPI are consistent with the strong domestic stimulative effects of China's government spending found in recent empirical studies (e.g Chen & Liu, 2018;Zhang et al, 2019)…”
supporting
confidence: 86%
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